Test React performance in two stages: run repeatable browser lab checks during development to catch regressions, then collect real-user field data to see what people experience in production. Track TTFB alongside the Core Web Vitals—LCP, INP, and CLS—but do not treat TTFB as a Core Web Vital or a Lighthouse score as a substitute for field measurement.
Which metrics should you test?
Core Web Vitals are Largest Contentful Paint (LCP), Interaction to Next Paint (INP), and Cumulative Layout Shift (CLS). Google’s good thresholds are assessed at the 75th percentile separately for mobile and desktop:
| Metric | Good threshold | What it helps assess |
|---|---|---|
| LCP | 2.5 seconds or less | How quickly the main content appears. |
| INP | 200 milliseconds or less | How responsive a page feels to user interactions. |
| CLS | 0.1 or less | How much visible content shifts unexpectedly. |
These thresholds come from Google’s Web Vitals guidance, updated October 31, 2024. They describe field performance, not a guaranteed outcome for a particular React app.
Time to First Byte (TTFB) measures the time from navigation start until the first response byte begins arriving. It is a supporting diagnostic metric, not a Core Web Vital. Google’s rough target is 0.8 seconds or less; whether TTFB is acceptable also depends on whether it is slowing the user-centered metrics that matter. See Optimize Time to First Byte, updated November 28, 2025.
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How do I test Core Web Vitals in a React app?
1. Choose representative routes and user flows
Test a production-like build on the routes that deliver meaningful content and the flows that exercise important interactive components. Include both initial page navigation and the interactions users rely on. A single landing-page check may miss a slow client-rendered route or an interaction that blocks the main thread.
2. Run controlled lab checks
Use Lighthouse in Chrome DevTools, the Lighthouse npm package, or Lighthouse CI to repeat checks as code changes. The Chrome DevTools Performance panel can also show live Core Web Vitals while you load and interact with a page. WebPageTest is useful when you need to reproduce a chosen device and network setup. Google describes these testing options in its Web Vitals guidance.
Keep test conditions consistent so a comparison reflects the code change rather than a changed setup. For each run, record:
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- The route and build being tested.
- Device emulation and network settings.
- Cache state and whether the test follows redirects.
- The interaction performed, if the route is interactive.
Lighthouse reports LCP and CLS. It reports Total Blocking Time (TBT) as a lab diagnostic related to responsiveness, but TBT is only a proxy for INP—not an INP measurement. INP depends on actual user interactions, which a standard non-interactive lab run cannot reproduce. Use lab results to spot regressions under controlled conditions, not to claim what real users’ INP is.
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3. Repeat the same route and flow across builds
Compare the same URL and interaction under the same device, network, and cache conditions. If a score changes, first check that the test setup did not change. Then inspect the affected metric and the route’s rendering or interaction behavior rather than relying on a single overall score.
How do I measure field performance?
Field data records experience from real users and complements lab checks. For a public page represented in the Chrome User Experience Report (CrUX), PageSpeed Insights can display field data. CrUX provides a broad view, but it does not generally give the detailed per-pageview telemetry needed to diagnose a specific regression.
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For ongoing page-level diagnosis, instrument real-user monitoring. Google’s field measurement guidance describes the web-vitals library as a production-ready wrapper around browser APIs and shows how onCLS, onINP, and onLCP can send measurements to an analytics endpoint.
Aggregate observations and assess the 75th percentile separately for mobile and desktop. That percentile represents the experience of most users more usefully than the best run on a developer’s machine. Field and lab results may differ because users have different devices and networks, encounter different redirects or cache states, see different content, and perform different interactions.
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How do I measure TTFB for a React website?
Measure navigation TTFB with browser timing data, Chrome DevTools, PageSpeed Insights, or the onTTFB callback from web-vitals. TTFB ends when the response begins to arrive; depending on the measurement context, it can include redirect and connection setup time. Google explains the metric and its measurement context in Optimize Time to First Byte.
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If server work appears to be the bottleneck, add a Server-Timing response header to expose backend stages. Compare readings carefully: a lab may reach a warm server-side cache, test a final URL without redirects, or use a network unlike the one a user has. When appropriate, check less common routes or cache-bypassing conditions—but ensure the test still represents a real user request.
Why can a fast TTFB still produce a slow React experience?
TTFB only tells you when the response starts arriving; it does not establish that the page is useful, visually complete, or responsive. This distinction matters for client-rendered React routes: the server can respond quickly while the browser still needs to download and execute JavaScript before meaningful content appears. Google notes that low TTFB is important for single-page applications where client rendering follows the initial markup.
Read TTFB alongside LCP, INP, and CLS. If TTFB is slow, investigate redirects, connection setup, server response time, and cache behavior. If TTFB is good but LCP or INP is poor, inspect client rendering, JavaScript work, and the interaction path instead of assuming the server response proves the page is fast.
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How should you interpret conflicting results?
If Lighthouse and PageSpeed Insights disagree, they may be measuring different conditions rather than contradicting each other. Lighthouse is a controlled lab check; PageSpeed Insights may also show field data from CrUX when available. Compare like with like, then investigate these differences:
- Device and network: lab emulation may not match the real-user mix.
- Redirects: a test of the final URL may omit time users spend being redirected.
- Cache: a warm server cache can make a lab result faster than a less common or uncached request.
- Content: personalized or variable content can alter what appears and when.
- Interaction: a lab run without the relevant user action cannot represent field INP.
- Route: the tested URL may not exercise the slow path or component users report.
Google’s TTFB guidance and Web Vitals guidance explain why measurement context matters. TTFB can help downstream loading metrics, particularly on client-rendered routes, but Google explicitly says it is not a Core Web Vitals metric and meeting its rough good threshold is not mandatory if it does not impede the metrics that matter.
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